Subject Areas :
akram mohammadi 1 , maasoomeh chaharmahal 2
1 - Department of Architectural Technology, Faculty of Fine Arts, University of Tehran
2 - West Tehran Branch,city planninig departement, Faculty of Architecture
Keywords:
Abstract :
References:
[1] Attia, A. and Salama, I.(2018),“Knowledge management capability and supply chain management practices in the Saudi food industry”, Business Process Management Journal, 24(2), pp. 459-477.
[2] Abdel-Basset, M., Manogaran, G. and Mohamed, M. (2018), “Internet of Things (IoT) and its impact on supply chain: a framework for building smart, secure and efficient systems”, Future Generation Computer Systems, Vol. 86, pp. 614-628
[3] Aina, Y.A. (2017), “Achieving smart sustainable cities with GeoICT support: the Saudi evolving smart cities”, Cities, Vol. 71, pp. 49-58
[4] Al-Hitmi, M. and Sherif, K. (2018), “Employee perceptions of fairness toward IoT monitoring”, VINE Journal of Information and Knowledge Management Systems, Vol. 48 No. 4, pp. 504-516.
[5] Ali, S.M., Rahman, M.H., Tumpa, T.J., Rifat, A.A.M. and Paul, S.K. (2018), “Examining price and service competition among retailers in a supply chain under potential demand disruption”, Journal of Retailing and Consumer Services, Vol. 40, pp. 40-47.
[6] Anandhi, S., Anitha, R. and Sureshkumar, V. (2016), “An RFID cloud authentication protocol for object tracking system in supply chain management”, Paper presented at the Annual Convention of the Computer Society of India
[7] Attia, A. and Salama, I. (2018), “Knowledge management capability and supply chain management practices in the Saudi food industry”, Business Process Management Journal, Vol. 24 No. 2, pp. 459-477.
[8] Azizi, R., Maleki, M., Moradi-Moghadam, M. and Cruz-Machado, V. (2016), “The impact of knowledge management practices on supply chain quality management and competitive advantages”, Management and Production Engineering Review, Vol. 7 No. 1, pp. 4-12. .
[9] Bagal, H.A., Soltanabad, Y.N., Dadjuo, M., Wakil, K. and Ghadimi, N. (2018), “Risk-assessment of photovoltaic-wind-battery-grid based large industrial consumer using information gap decision theory”, Solar Energy, Vol. 169, pp. 343-352.
[10] Chin, W.W. and Dibbern, J. (2010), “An introduction to a permutation based procedure for multi-group PLS analysis: results of tests of differences on simulated data and a cross cultural analysis of the sourcing of information system services between Germany and the USA”, In Handbook of Partial Least Squares, Springer, pp. 171-193
[11] Fernandes, C., Ferreira, J.J. and Marques, C.S. (2015), “Innovation management capabilities in rural and urban knowledge intensive business services: empirical evidence”, Service Business, Vol. 9 No. 2, pp. 233-256.
[12] Fouladi, P. and Jafari Navimipour, N. (2017), “Human resources ranking in a cloud-based knowledge sharing framework using the quality control criteria”, Kybernetes, Vol. 46 No. 5, pp. 876-892.
[13] Gou, J., Li, N., Lyu, T., Lyu, X. and Zhang, Z. (2019), “Barriers of knowledge transfer and mitigating strategies in collaborative management system implementations”, VINE Journal of Information and Knowledge Management Systems, Vol. 49 No. 1, pp. 2-20
[14] Green, G., Liu, L. and Qi, B. (2009), “Knowledge-based management information systems for the effective business performance of SMEs”, Journal of International Technology and InformationManagement, Vol. 18 No. 2, p. 201.
[15] Hair, J. F., Hult, G. T. M., Ringle, C. M.(2021) Partial Least Squares Structural Equation Modeling, 3nd Edition, Sage Publications Inc., Thousand Oaks, CA.
[16] Hall, Stuart (1997). The Work of Representation, In Cultural Representation and Signifying Practice, Sage Publication.
[17] Harrison, C., Eckman, B., Hamilton, R., Hartswick, P., Kalagnanam, J., Paraszczak, J., Williams, P.,(2010). Foundations for smarter cities. IBM J. Res. Dev. 54 (4), 1–16.
[18] Hult, G.T.M., Ketchen, D.J. and Arrfelt, M. (2007), “Strategic supply chain management: improving performance through a culture of competitiveness and knowledge development”, Strategic Management Journal, Vol. 28 No. 10, pp. 1035-1052.
[19] Jalalifar, S., Hafshejani, K.F. and Movahedi, M. (2013), “Evaluation of the effective barriers in GSCM implementation using DEMATEL method (case study: Iran Khodro CO)”. Nature and Science, Vol. 11 No. 11, pp. 95-102.
[20] Jnr, B.A., Majid, M.A. and Romli, A. (2018), “A trivial approach for achieving smart city: a way forward towards a sustainable society”, Paper presented at the 2018 21st Saudi Computer Society National Computer Conference (NCC).
[21] Kaliani Sundram, V.P., Chandran, V. and Awais Bhatti, M. (2016), “Supply chain practices and performance: the indirect effects of supply chain integration”, Benchmarking: An International Journal, Vol. 23 No. 6, pp. 1445-1471
[22] Kamble, S.S., Gunasekaran, A., Parekh, H. and Joshi, S. (2019), “Modeling the internet of things adoption barriers in food retail supply chains”, Journal of Retailing and Consumer Services, Vol. 48, pp. 154-168.
[23] Khodaei, H., Hajiali, M., Darvishan, A., Sepehr, M. and Ghadimi, N. (2018), “Fuzzy-based heat and power hub models for cost-emission operation of an industrial consumer using compromise programming”, Applied Thermal Engineering, Vol. 137, pp. 395-405.
[24] Kochan, C.G., Nowicki, D.R., Sauser, B. and Randall, W.S. (2018), “Impact of cloud-based information sharing on hospital supply chain performance: a system dynamics framework”, International Journal of Production Economics, Vol. 195, pp. 168-185.
[25] Kopczak, L.R. and Johnson, M.E. (2003), ‘The Supply-chain Management Effect’, MIT Sloan Management Review, 44(3): pp.27-40
[26] Małecki, K., Iwan, S. and Kijewska, K. (2014), “Influence of intelligent transportation systems on reduction of the environmental negative impact of urban freight transport based on Szczecin example”, Procedia – Social and Behavioral Sciences, Vol. 151, pp. 215-229.
[27] Małecki, K., Iwan, S., & Kijewska, K. (2014). Influence of Intelligent Transportation Systems on Reduction of the Environmental Negative Impact of Urban Freight Transport Based on Szczecin Example. Procedia - Social and Behavioral Sciences, 151, pp.215–229.
[28] Navimipour, N.J. and Charband, Y. (2016), “Knowledge sharing mechanisms and techniques in project teams: literature review, classification, and current trends”, Computers in Human Behavior, Vol. 62, pp. 730-742.
[29] Ngai, E. W. T., Cheng, T. C. E., & Ho, S. S. M. (2004). Critical success factors of web-based supply-chain management systems: an exploratory study. Production Planning & Control, 15(6),pp. 622–630
[30] Opczak, L.R. and Johnson, M.E. (2003), ‘The Supply-chain Management Effect’, MIT Sloan Management Review, 44(3): pp.27-40
[31] Papert, M. and Pflaum, A. (2017), “Development of an ecosystem model for the realization of internet of things (IoT) services in supply chain management”, Electronic Markets, Vol. 27 No. 2, pp. 175-189.
[32] Rymaszewska, A., Helo, P. and Gunasekaran, A. (2017), “IoT powered servitization of manufacturing – an exploratory case study”, International Journal of Production Economics, Vol. 192, pp. 92-105.
[33] Silva, B.N., Khan, M., Han, K., Han, (2018). Towards sustainable smart cities: a review of trends, architectures, components, and open challenges in smart cities. Sustainable Cities and Society 38, 697–713.
[34] Tenenhaus, M., Esposito Vinzi, V., Chatelin, Y.-M., & Lauro, C. (2005). PLS path modeling. Computational Statistics & Data Analysis, 48(1), 159–205.
[35] Werts, C. E., Linn, R. L., & Jöreskog, K. G. (1974). Intraclass Reliability Estimates: Testing Structural Assumptions. Educational and Psychological Measurement, 34(1), 25-33
[36] Wetzels, M., Odekerken-Schorder, G., & Van Oppen, C. (2009) Using PLS Path Modeling for Assessing Hierarchical Construct Models: Guidelines and Empirical Illustration, MIS Quarterly, 33, (33), 177-1.
[37] Wu, Y., Cegielski, C.G., Hazen, B.T. and Hall, D.J. (2013), “Cloud computing in support of supply chain information system infrastructure: understanding when to go to the cloud”, Journal of Supply Chain Management, Vol. 49 No. 3, pp. 25-41.
[38] Zhu, L., Yu, F.R., Wang, Y., Ning, B. and Tang, T. (2018), “Big data analytics in intelligent transportation systems: a survey”, IEEE Transactions on Intelligent Transportation Systems, No. 99, pp. 1-16.
[1] Attia, A. and Salama, I.(2018),“Knowledge management capability and supply chain management practices in the Saudi food industry”, Business Process Management Journal, 24(2), pp. 459-477.
[2] Abdel-Basset, M., Manogaran, G. and Mohamed, M. (2018), “Internet of Things (IoT) and its impact on supply chain: a framework for building smart, secure and efficient systems”, Future Generation Computer Systems, Vol. 86, pp. 614-628
[3] Aina, Y.A. (2017), “Achieving smart sustainable cities with GeoICT support: the Saudi evolving smart cities”, Cities, Vol. 71, pp. 49-58
[4] Al-Hitmi, M. and Sherif, K. (2018), “Employee perceptions of fairness toward IoT monitoring”, VINE Journal of Information and Knowledge Management Systems, Vol. 48 No. 4, pp. 504-516.
[5] Ali, S.M., Rahman, M.H., Tumpa, T.J., Rifat, A.A.M. and Paul, S.K. (2018), “Examining price and service competition among retailers in a supply chain under potential demand disruption”, Journal of Retailing and Consumer Services, Vol. 40, pp. 40-47.
[6] Anandhi, S., Anitha, R. and Sureshkumar, V. (2016), “An RFID cloud authentication protocol for object tracking system in supply chain management”, Paper presented at the Annual Convention of the Computer Society of India
[7] Attia, A. and Salama, I. (2018), “Knowledge management capability and supply chain management practices in the Saudi food industry”, Business Process Management Journal, Vol. 24 No. 2, pp. 459-477.
[8] Azizi, R., Maleki, M., Moradi-Moghadam, M. and Cruz-Machado, V. (2016), “The impact of knowledge management practices on supply chain quality management and competitive advantages”, Management and Production Engineering Review, Vol. 7 No. 1, pp. 4-12. .
[9] Bagal, H.A., Soltanabad, Y.N., Dadjuo, M., Wakil, K. and Ghadimi, N. (2018), “Risk-assessment of photovoltaic-wind-battery-grid based large industrial consumer using information gap decision theory”, Solar Energy, Vol. 169, pp. 343-352.
[10] Chin, W.W. and Dibbern, J. (2010), “An introduction to a permutation based procedure for multi-group PLS analysis: results of tests of differences on simulated data and a cross cultural analysis of the sourcing of information system services between Germany and the USA”, In Handbook of Partial Least Squares, Springer, pp. 171-193
[11] Fernandes, C., Ferreira, J.J. and Marques, C.S. (2015), “Innovation management capabilities in rural and urban knowledge intensive business services: empirical evidence”, Service Business, Vol. 9 No. 2, pp. 233-256.
[12] Fouladi, P. and Jafari Navimipour, N. (2017), “Human resources ranking in a cloud-based knowledge sharing framework using the quality control criteria”, Kybernetes, Vol. 46 No. 5, pp. 876-892.
[13] Gou, J., Li, N., Lyu, T., Lyu, X. and Zhang, Z. (2019), “Barriers of knowledge transfer and mitigating strategies in collaborative management system implementations”, VINE Journal of Information and Knowledge Management Systems, Vol. 49 No. 1, pp. 2-20
[14] Green, G., Liu, L. and Qi, B. (2009), “Knowledge-based management information systems for the effective business performance of SMEs”, Journal of International Technology and InformationManagement, Vol. 18 No. 2, p. 201.
[15] Hair, J. F., Hult, G. T. M., Ringle, C. M.(2021) Partial Least Squares Structural Equation Modeling, 3nd Edition, Sage Publications Inc., Thousand Oaks, CA.
[16] Hall, Stuart (1997). The Work of Representation, In Cultural Representation and Signifying Practice, Sage Publication.
[17] Harrison, C., Eckman, B., Hamilton, R., Hartswick, P., Kalagnanam, J., Paraszczak, J., Williams, P.,(2010). Foundations for smarter cities. IBM J. Res. Dev. 54 (4), 1–16.
[18] Hult, G.T.M., Ketchen, D.J. and Arrfelt, M. (2007), “Strategic supply chain management: improving performance through a culture of competitiveness and knowledge development”, Strategic Management Journal, Vol. 28 No. 10, pp. 1035-1052.
[19] Jalalifar, S., Hafshejani, K.F. and Movahedi, M. (2013), “Evaluation of the effective barriers in GSCM implementation using DEMATEL method (case study: Iran Khodro CO)”. Nature and Science, Vol. 11 No. 11, pp. 95-102.
[20] Jnr, B.A., Majid, M.A. and Romli, A. (2018), “A trivial approach for achieving smart city: a way forward towards a sustainable society”, Paper presented at the 2018 21st Saudi Computer Society National Computer Conference (NCC).
[21] Kaliani Sundram, V.P., Chandran, V. and Awais Bhatti, M. (2016), “Supply chain practices and performance: the indirect effects of supply chain integration”, Benchmarking: An International Journal, Vol. 23 No. 6, pp. 1445-1471
[22] Kamble, S.S., Gunasekaran, A., Parekh, H. and Joshi, S. (2019), “Modeling the internet of things adoption barriers in food retail supply chains”, Journal of Retailing and Consumer Services, Vol. 48, pp. 154-168.
[23] Khodaei, H., Hajiali, M., Darvishan, A., Sepehr, M. and Ghadimi, N. (2018), “Fuzzy-based heat and power hub models for cost-emission operation of an industrial consumer using compromise programming”, Applied Thermal Engineering, Vol. 137, pp. 395-405.
[24] Kochan, C.G., Nowicki, D.R., Sauser, B. and Randall, W.S. (2018), “Impact of cloud-based information sharing on hospital supply chain performance: a system dynamics framework”, International Journal of Production Economics, Vol. 195, pp. 168-185.
[25] Kopczak, L.R. and Johnson, M.E. (2003), ‘The Supply-chain Management Effect’, MIT Sloan Management Review, 44(3): pp.27-40
[26] Małecki, K., Iwan, S. and Kijewska, K. (2014), “Influence of intelligent transportation systems on reduction of the environmental negative impact of urban freight transport based on Szczecin example”, Procedia – Social and Behavioral Sciences, Vol. 151, pp. 215-229.
[27] Małecki, K., Iwan, S., & Kijewska, K. (2014). Influence of Intelligent Transportation Systems on Reduction of the Environmental Negative Impact of Urban Freight Transport Based on Szczecin Example. Procedia - Social and Behavioral Sciences, 151, pp.215–229.
[28] Navimipour, N.J. and Charband, Y. (2016), “Knowledge sharing mechanisms and techniques in project teams: literature review, classification, and current trends”, Computers in Human Behavior, Vol. 62, pp. 730-742.
[29] Ngai, E. W. T., Cheng, T. C. E., & Ho, S. S. M. (2004). Critical success factors of web-based supply-chain management systems: an exploratory study. Production Planning & Control, 15(6),pp. 622–630
[30] Opczak, L.R. and Johnson, M.E. (2003), ‘The Supply-chain Management Effect’, MIT Sloan Management Review, 44(3): pp.27-40
[31] Papert, M. and Pflaum, A. (2017), “Development of an ecosystem model for the realization of internet of things (IoT) services in supply chain management”, Electronic Markets, Vol. 27 No. 2, pp. 175-189.
[32] Rymaszewska, A., Helo, P. and Gunasekaran, A. (2017), “IoT powered servitization of manufacturing – an exploratory case study”, International Journal of Production Economics, Vol. 192, pp. 92-105.
[33] Silva, B.N., Khan, M., Han, K., Han, (2018). Towards sustainable smart cities: a review of trends, architectures, components, and open challenges in smart cities. Sustainable Cities and Society 38, 697–713.
[34] Tenenhaus, M., Esposito Vinzi, V., Chatelin, Y.-M., & Lauro, C. (2005). PLS path modeling. Computational Statistics & Data Analysis, 48(1), 159–205.
[35] Werts, C. E., Linn, R. L., & Jöreskog, K. G. (1974). Intraclass Reliability Estimates: Testing Structural Assumptions. Educational and Psychological Measurement, 34(1), 25-33
[36] Wetzels, M., Odekerken-Schorder, G., & Van Oppen, C. (2009) Using PLS Path Modeling for Assessing Hierarchical Construct Models: Guidelines and Empirical Illustration, MIS Quarterly, 33, (33), 177-1.
[37] Wu, Y., Cegielski, C.G., Hazen, B.T. and Hall, D.J. (2013), “Cloud computing in support of supply chain information system infrastructure: understanding when to go to the cloud”, Journal of Supply Chain Management, Vol. 49 No. 3, pp. 25-41.
[38] Zhu, L., Yu, F.R., Wang, Y., Ning, B. and Tang, T. (2018), “Big data analytics in intelligent transportation systems: a survey”, IEEE Transactions on Intelligent Transportation Systems, No. 99, pp. 1-16.
